Skip to content

chaitanyakasaraneni/machineTranslationApp

 
 

Repository files navigation

English to Telugu Video Translator

About this project

Initial version was developed as part of UC Berkeley Open Innovation Hackathon, India - 2017 (Winner project in Communications vertical) and later underwent various improvements as a part of major project during our undergrad. This application mainly focuses on translation of English videos into Telugu.

Published Paper:

Overview

In spite of many languages being spoken in India, it is difficult for the people to understand foreign languages like English, Spanish, Italian, etc. The recognition and synthesis of speech are prominent emerging technologies in natural language processing and communication domains. This paper aims to leverage the open source applications of these technologies, machine translation, text-to-speech system (TTS), and speech-to-text system (STT) to convert available online resources to Indian languages. This application takes an English language video as an input and separates the audio from video. It then divides the audio file into several smaller chunks based on the timestamps. These audio chunks are then individually converted into text using IBM Watson’s speech-to- text (STT) module. The obtained text chunks are then concatenated and passed to Google’s machine translate API for conversion to the requested Indian language. After this translation, a TTS system is required to convert the text into the desired audio output. Not many open source TTS systems are available for Indian regional languages. One such available application is the flite engine (a lighter version of Festival engine developed by Prof. Alan Black at Carnegie Mellon University (CMU)). This flite engine is used as TTS for generating audio from translated text. This application is beneficial to visually impaired people as well as individuals who are not capable of reading text to acquire knowledge in their native language. In future, this application aims to achieve ubiquitous communication enabling people of different regions to communicate with each other breaking the language barriers.

Technologies & APIs used

  • ffmpeg, pydub and other libraries for raw video/audio processing and segmentation.
  • IBM Watson, Google Translate APIs for Speech-to-Text & translation.
  • CMU Festival (flite) for Telugu Text-to-Speech.

apis

Work-flow of the project

The project development involved three stages.

  • Audio extraction from video
  • Processing the threads parallelly
  • Text-to-Speech and merging stages

Installation and working

Clone the repository by using the following command

git clone https://github.com/chaitanyakasaraneni/capstoneproject.git

Then headover to the CMU's flite repo and clone that using:

git clone http://github.com/festvox/flite

After cloning the repo, use the following commands to install the flite engine:

cd flite
./configure
make
make get_voices

For the usage instructions head over to the flite repo and refer the USAGE section

Releases

No releases published

Packages

No packages published

Languages

  • Python 99.0%
  • Shell 1.0%